|ชื่อเรื่อง||:||Burden of disease attributed to ambient air pollution in Thailand: A GIS-based approach|
|นักวิจัย||:||Chayut Pinichka , Nuttapat Makka , Decharut Sukkumnoed , Suwat Chariyalertsak , Puchong Inchai , Kanitta Bundhamcharoen|
|อ้างอิง||:||19326203 , 2-s2.0-85038910715 , 10.1371/journal.pone.0189909 , https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85038910715&origin=inward , http://cmuir.cmu.ac.th/jspui/handle/6653943832/43451|
© 2017 Pinichka et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background Growing urbanisation and population requiring enhanced electricity generation as well as the increasing numbers of fossil fuel in Thailand pose important challenges to air quality management which impacts on the health of the population. Mortality attributed to ambient air pollution is one of the sustainable development goals (SDGs). We estimated the spatial pattern of mortality burden attributable to selected ambient air pollution in 2009 based on the empirical evidence in Thailand. Methods We estimated the burden of disease attributable to ambient air pollution based on the comparative risk assessment (CRA) framework developed by the World Health Organization (WHO) and the Global Burden of Disease study (GBD). We integrated geographical information systems (GIS)-based exposure assessments into spatial interpolation models to estimate ambient air pollutant concentrations, the population distribution of exposure and the concentration-response (CR) relationship to quantify ambient air pollution exposure and associated mortality. We obtained air quality data from the Pollution Control Department (PCD) of Thailand surface air pollution monitoring network sources and estimated the CR relationship between relative risk (RR) and concentration of air pollutants from the epidemiological literature. Results We estimated 650–38,410 ambient air pollution-related fatalities and 160–5,982 fatalities that could have been avoided with a 20 reduction in ambient air pollutant concentrations. The summation of population-attributable fraction (PAF) of the disease burden for all-causes mortality in adults due to NO 2 and PM 2.5 were the highest among all air pollutants at 10% and 7.5%, respectively. The PAF summation of PM 2.5 for lung cancer and cardiovascular disease were 16.8% and 14.6% respectively and the PAF summations of mortality attributable to PM 10 was 3.4% for all-causes mortality, 1.7% for respiratory and 3.8% for cardiovascular mortality, while the PAF summation of mortality attributable to NO 2 was 7.8% for respiratory mortality in Thailand. Conclusion Mortality due to ambient air pollution in Thailand varies across the country. Geographical distribution estimates can identify high exposure areas for planners and policy-makers. Our results suggest that the benefits of a 20% reduction in ambient air pollution concentration could prevent up to 25% of avoidable fatalities each year in all-causes, respiratory and cardiovascular categories. Furthermore, our findings can provide guidelines for future epidemiological investigations and policy decisions to achieve the SDGs.
Chayut Pinichka , Nuttapat Makka , Decharut Sukkumnoed , Suwat Chariyalertsak , Puchong Inchai , Kanitta Bundhamcharoen . (2560). Burden of disease attributed to ambient air pollution in Thailand: A GIS-based approach.
เชียงใหม่ : มหาวิทยาลัยเชียงใหม่ .
Chayut Pinichka , Nuttapat Makka , Decharut Sukkumnoed , Suwat Chariyalertsak , Puchong Inchai , Kanitta Bundhamcharoen . 2560. "Burden of disease attributed to ambient air pollution in Thailand: A GIS-based approach".
เชียงใหม่ : มหาวิทยาลัยเชียงใหม่ .
Chayut Pinichka , Nuttapat Makka , Decharut Sukkumnoed , Suwat Chariyalertsak , Puchong Inchai , Kanitta Bundhamcharoen . "Burden of disease attributed to ambient air pollution in Thailand: A GIS-based approach."
เชียงใหม่ : มหาวิทยาลัยเชียงใหม่ , 2560. Print.